Rockfall Modelling in Forested Areas: The Role of Digital Terrain Model Grid Cell Size

Žabota, Barbara; Mikoš, Matjaž; Kobal, Milan

doi:10.3390/app11041461

Cited by 7 publications

(9 citation statements)

References 56 publications

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“…The rockfall source area is represented by a vertical rocky (fall height 150 m), west-facing cliff. On the rockfall slope, it is possible to observe that rockfall activity has been present for longer time periods (older rocks and changed vegetation cover in comparison to the majority of the slope), while the last larger rockfall event at this site occurred in April 2017 [58] when approximately 29,000 m 3 of rock material was released. The majority of the material was deposited directly below the rock cliff, while individual fragmented rocks were transported further down the slope affecting diminishing parts of the forest and causing different injuries to other trees.…”

Section: Study Sitesmentioning

confidence: 80%

“…The rockfall source area is represented by a vertical rocky (fall height 150 m), west-facing cliff. On the rockfall slope, it is possible to observe that rockfall activity has been present for longer time periods (older rocks and changed vegetation cover in comparison to the majority of the slope), while the last larger rockfall event at this site occurred in April 2017 [58] when approximately 29,000 Sites that are located in the Trenta Valley are geotectonically part of the Southern Alps and part of the Julian Alps Overthrust [50][51][52]. Fractures in this area have dominant transversal Dinaric (NE-SW) and Dinaric directions (NE-SE) [53].…”

Section: Study Sitesmentioning

confidence: 83%

“…Part of the forested area has been affected by the larger rockfall in April 2012 when part of the forest cover was completely diminished, and rocks of various volumes stopped in the forested area, causing injuries of different sizes. The latest larger event at the site occurred in March 2020 when approximately 11,000 m 3 [58] of material collapsed from the rock cliff. The majority of rockfall deposits reached volumes up to 3 m 3 .…”

Section: Study Sitesmentioning

confidence: 99%

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The Use of UAV-Acquired Multiband Images for Detecting Rockfall-Induced Injuries at Tree Crown Level

Žabota

Kobal

2022

Forests

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In this paper, we present an identification of rockfall-injured trees based on multiband images obtained by an unmanned aerial vehicle (UAV). A survey with a multispectral camera was performed on three rockfall sites with versatile tree species (Fagus sylvatica L., Larix decidua Mill., Pinus sylvestris L., Picea abies (L.) Karsten, and Abies alba Mill.) and with different characterizations of rockfalls and rockfall-induced injuries. At one site, rockfall injuries were induced in the same year as the survey. At the second site, they were induced one year after the initial injuries, and at the third site, they were induced six years after the first injuries. At one site, surveys were performed three years in a row. Multiband images were used to extract different vegetation indices (VIs) at the tree crown level and were further studied to see which VIs can identify the injured trees and how successfully. A total of 14 VIs were considered, including individual multispectral bands (green, red, red edge, and near-infrared) by using regression models to differentiate between the injured and uninjured groups for a single year and for three consecutive years. The same model was also used for VI differentiations among the recorded injury groups and size of the injuries. The identification of injured trees based on VIs was possible at the sites where rockfall injuries were induced at least one year before the UAV survey, and they could still be identifiable six years after the initial injuries. At the site where injuries were induced only four months before the UAV survey, the identification of injured trees was not possible. VIs that could explain the largest variability (R2 > 0.3) between injured and uninjured trees were: inverse ratio index (IRVI), green–red vegetation index (GRVI), normalized difference vegetation index (NDVI), normalized ratio index (NRVI), and ratio vegetation index (RVI). RVI was the most successful, explaining 40% of the variance at two sites. R2 values only increased by a few percentages (up to 10%) when the VIs of injured trees were observed over a period of three years and mostly did not change significantly, thus not indicating if the vitality of the trees increased or decreased. Differentiation among the injured groups did not show promising results, while, on the other hand, there was a strong correlation between the VI values (RVI) and the size of the injury according to the basal area of the trees (so-called injury index). Both in the case of broadleaves and conifers at two sites, the R2 achieved a value of 0.82. The presented results indicate that the UAV-acquired multiband images at the tree crown level can be used for surveying rockfall protection forests in order to monitor their vitality, which is crucial for maintaining the protective effect through time and space.

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Section: Study Sitesmentioning

confidence: 80%

“…The rockfall source area is represented by a vertical rocky (fall height 150 m), west-facing cliff. On the rockfall slope, it is possible to observe that rockfall activity has been present for longer time periods (older rocks and changed vegetation cover in comparison to the majority of the slope), while the last larger rockfall event at this site occurred in April 2017 [58] when approximately 29,000 Sites that are located in the Trenta Valley are geotectonically part of the Southern Alps and part of the Julian Alps Overthrust [50][51][52]. Fractures in this area have dominant transversal Dinaric (NE-SW) and Dinaric directions (NE-SE) [53].…”

Section: Study Sitesmentioning

confidence: 83%

Section: Study Sitesmentioning

confidence: 99%

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The Use of UAV-Acquired Multiband Images for Detecting Rockfall-Induced Injuries at Tree Crown Level

Žabota

Kobal

2022

Forests

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“…Spatially explicit simulations of forest effects on rockfall require threedimensional models that account for the effects of individual trees on kinetic energy dissipation, lateral rebound and impact [40]. Therefore, three-dimensional trajectory models have been developed to simulate block dispersion depending on the topography of the terrain rather than just on a set of several two-dimensional trajectories [25,[41][42][43]; however, only few consider the protective effect of forest, e.g., Rockyfor3D by a reduction in kinetic energy dependent on stem diameter and the percentage of coniferous trees [44]. In RAMMS::ROCKFALL, non-smooth Modeling Protective Forests for Gravitational Natural Hazards and How It Relates to Risk-Based… DOI: http://dx.doi.org/10.5772/intechopen.99510 mechanics are coupled with hard contact laws in the framework of a discrete element model; the plugin to simulate the effect of forest on rockfall trajectories will be released in fall of 2021 [45].…”

Section: Rockfall Trajectory Models At the Slope Scale And Integratio...mentioning

confidence: 99%

Modeling Protective Forests for Gravitational Natural Hazards and How It Relates to Risk-Based Decision Support Tools

D'Amboise¹,

Teich²,

Hormes³

et al. 2022

Protective Forests as Ecosystem-Based Solution for Disaster Risk Reduction (Eco-Drr)

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Simulation tools and their integrated models are widely used to estimate potential starting, transit and runout zones of gravitational natural hazards such as rockfall, snow avalanches and landslides (i.e., gravitational mass flows [GMFs]). Forests growing in areas susceptible to GMFs can influence their release and propagation probabilities (i.e., frequency and magnitude of an event) as well as their intensity. If and how well depends on the GMF type, the topography of the terrain and the forests’ structure. In this chapter, we introduce basic concepts of computer models and state-of-the-art methods for modeling forest interactions with rockfall, snow avalanches and landslides. Furthermore, an example of a protective forest routine embedded in the runout angle-based GMF simulation tool Flow-Py will be presented together with its parameterization for forest-GMF interactions. We applied Flow-Py and two custom extensions to model where forests protect people and assets against GMFs (the protective function) and how forests reduce their frequency, magnitude and/or intensity (the protective effect). The goal of this chapter is to describe protective forest models, so that practitioners and decision makers can better utilize them and their results as decision support tools for risk-based protective forest and ecosystem-based integrated risk management of natural hazards.

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“…A range of rockfall models were developed in order to assess rockfalls in terms of dynamics, trajectories, kinetic energy, velocity and jump height and many other aspects (Azzoni et al 1995, Dorren 2003, Volkwein et al 2011, Frattini et al 2012, Žabota et al 2021, Liu et al 2021. RAMMS, CONEFALL, STONE, Georock, Rockyfor3D, FlowR and Rotomap produce two-dimensional (2D) and 3D rockfall models based on different algorithms and GIS for spatial analysis (Guzzetti et al 2002, Topal et al 2012, Bartelt et al 2016a).…”

Section: Rockfall Simulationsmentioning

confidence: 99%

Evaluation of Rockfall Hazard Based On UAV Technology And 3D Rockfall Simulations

Utlu

Öztürk

Şimşek

2021

Preprint

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In this study, the rockfall hazard in Hacıabdullah village located in the Central Anatolia region of Turkey was assessed with three-dimensional (3D) rockfall analyses based on unmanned aerial vehicle (UAV) technology using RAMMS (Rockfall software). With several rockfall disasters experienced in the village, the final event occurred in 2008, and several houses were evacuated due to rockfall risk after this event. A total of 17 hanging blocks with fall potential were identified and block dimension measurements were performed during field studies. In order to assess the rockfall hazard in the study area, digital surface model (DSM) data were obtained using high-resolution images obtained by UAV. According to dimensional values, the geometric and volumetric features of each rock were assessed close to reality with the RAMMS 3D rockfall modeling program. As a result of 3-D rockfall modelling, the maximum kinetic energy, maximum velocity, and maximum jump height of the falling blocks are reached to 3476 kJ, 23.1 m/s, and 14.57 m, respectively. The shape and volume of the blocks, as well as the slope features, rocks display differences in their runout distances after falls. A rock block with equant geometry has a runout distance of 53.1-126.9 m, whereas a rock block with flat or long geometry has a runout distance of 34-122.9 m. Rocks that do not move very far from the source area are; in other words, where the free-fall process is dominant, may significantly damage the roads. However, rolling blocks, in other words, blocks which can travel long distances from the source area, have a potential to cause great damage at the settlement areas, roads and trees. According to the hazard map, R6, R12, R13, R14, R15, R16, and R17 blocks involve high and moderate levels of risk for settlement units. R1, R4, R7, R8, R9, and R10 blocks show that the majority of them involve low risk, while a small portion is a moderate risk.

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Rockfall Modelling in Forested Areas: The Role of Digital Terrain Model Grid Cell Size

Cited by 7 publications

References 56 publications

The Use of UAV-Acquired Multiband Images for Detecting Rockfall-Induced Injuries at Tree Crown Level

The Use of UAV-Acquired Multiband Images for Detecting Rockfall-Induced Injuries at Tree Crown Level

Modeling Protective Forests for Gravitational Natural Hazards and How It Relates to Risk-Based Decision Support Tools

Evaluation of Rockfall Hazard Based On UAV Technology And 3D Rockfall Simulations

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